Leaf area index (LAI) is a primary parameter for characterizing vegetation canopy structure. Since LAI can affect many vegetation ecological processes, such as transpiration, interception and energy exchange, it is used as a critical input for ecological models and land surface process models. At present, several global LAI datasets have been generated from different satellite remote sensing data, such as AVHRR, MODIS and VEGETATION, by different retrieval methods. MODIS, CYCLOPES and GLASS LAI datasets are those with higher spatial and temporal resolution. The spatial and temporal consistency of MODIS, CYCLOPES and GLASS LAI datasets was analyzed over Hanjiang River basin, which is covered with several vegetation types. Comparative study revealed the following characteristics: ① CYCLOPES LAI was observed to contain a large number of missing pixels, while MODIS and GLASS LAI products were more spatially and temporally complete. MODIS LAI contained many invalid pixels, whose LAI became much smaller abruptly in comparison with the LAI values just before or after this time. ② The spatial distributions of MODIS, CYCLOPES and GLASS LAI were mainly consistent with the vegetation types of the basin. The spatial distributions of MODIS and GLASS LAI were more consistent than those of CYCLOPES LAI. MODIS LAI was larger than GLASS LAI in forest pixels, while it was contrary in other pixels. CYCLOPES LAI was much smaller than MODIS and GLASS LAI in forest pixels. ③ MODIS, CYCLOPES and GLASS LAI products generally depicted similar temporal trajectories. GLASS LAI had the smoothest and completest trajectories, while the trajectories of MODIS LAI contained a large number of erratic fluctuations. All of these three LAI products depicted similar seasonal changes for different vegetation types. Compared with CYCLOPES LAI, a good agreement was achieved between MODIS and GLASS LAI values.
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2018, Vol. 30 
), 周买春(
